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Click here or scroll down to respond to this candidate Candidate's Name
PHONE NUMBER AVAILABLE| EMAIL AVAILABLE
Experienced Systems Software Engineer with a strong background in designing, implementing, and managing
large-scale distributed systems. Skilled at analyzing infrastructure needs, developing automation scripts, and
delivering effective solutions. Adept at collaborating with cross-functional teams and fostering positive working
relationships. Committed to continuous learning and leveraging technology to solve complex challenges.
PROFESSIONAL EXPERIENCE
Associate Consultant | Atos Syntel, Chennai, India May 2021 Aug. 2022
Spearheaded optimization efforts for PeopleSoft Finance (FSCM) modules, focusing on Accounts
Receivables and Billing, resulting in enhanced operational efficiency.
Orchestrated critical setups within PeopleSoft Finance, including business unit structures, tax codes, and
locations, leading to a notable improvement in the billing process speed.
Successfully implemented GST setup in Billing Module, ensuring compliance and reducing error rates by
20%.
Demonstrated expertise in Application Designer, PS Query, and MS SQL Server, streamlining processes
and significantly reducing query response time.
Played a pivotal role as a Business Analyst, effectively bridging client requirements with development
teams, resulting in increased client satisfaction.
Contributed to system design, testing, and implementation processes, ensuring a seamless transition, and
minimizing post-implementation issues.
Managed non-routine processing and change requests related to client initiatives, resolving issues promptly
to maintain project timelines and client satisfaction.
Built and maintained positive working relationships with internal and external stakeholders, fostering a
collaborative environment conducive to project success.
Managed internal and external project communications, providing regular updates, and ensuring
transparency.
Assisted in training internal teams on new processes or technologies, contributing to the development and
growth of team members.
Prepared and maintained detailed project artifacts, including plans, status reports, and meeting minutes,
ensuring accurate documentation and project traceability.
Project G Client: Syntel Global
Technologies: PeopleSoft Financials and SCM, People Tools 8.54, MS SQL Server
Led the development and implementation of new modules across global subsidiaries, resulting in a significant
increase in operational efficiency.
Resolved support tickets within SLA, maintaining a 95% resolution rate for varying nature issues (P1-P4) in
FSCM modules.
Conducted requirement gathering sessions to develop billing modules tailored to customer specifications,
ensuring alignment with organizational goals.
Provided PeopleSoft production support and implemented customizations based on client requirements,
contributing to system stability and functionality.
Analyzed and customized delivered pages and processes to align with organizational and client needs,
enhancing overall system performance and usability.
KLUNIVERSITY|Student Assistant Jan 2019 May 2019
Conducted sentiment analysis on a large dataset of Amazon reviews using Natural Language Processing
(NLP) techniques and machine learning algorithms.
Preprocessed collected data using techniques such as tokenization, POS tagging, stemming, lemmatizing,
and SentiWordNet analysis to enhance the accuracy of sentiment analysis.
Developed and implemented N-gram models (uni-grams, bi-grams, and tri-grams) to capture the context
and semantics of text for improved sentiment classification.
Evaluated sentiment analysis models using metrics such as precision, recall, F-score, and AUC curve,
demonstrating proficiency in model evaluation and performance assessment.
Conducted literature review on sentiment analysis tasks and techniques, staying abreast of the latest
research studies and advancements in the field.
Collaborated with a multidisciplinary team of researchers and analysts to discuss and refine methodologies
for sentiment analysis, ensuring comprehensive and accurate results.
Presented findings and insights from sentiment analysis projects to stakeholders, including detailed analysis
reports and visualizations, contributing to data-driven decision-making processes.
Demonstrated strong analytical and problem-solving skills in resolving challenges encountered during
sentiment analysis tasks, such as handling diverse datasets and optimizing model performance.
Implemented a logistic regression classifier to accurately predict the polarities of product reviews, achieving an
impressive accuracy rate of 91.6%.
Utilized web scraping techniques to collect real-time data from various online sources, including social
media platforms like Twitter, for sentiment analysis.
Programming Languages: Python
Web Technologies: HTML, CSS, JavaScript
Databases: MS-SQL Server, MySQL, MongoDB
Data Visualization & Analytical Tools: Tableau, Power BI, PeopleSoft Query, Process Scheduler
Functional Knowledge: Billing, Account Receivables, Timesheet, Business Unit Setups, Customer Setups,
Account Code Setups, TAX setups, VAT Setups, Security Access, Permission Lists,GST setup, Project
Module, Security.
Development Environments & Tools: VS Code, App Designer (PS), Application Engine, Data Mover
Report Awarness: Crystal Report, PS Query
Operating Systems: Windows
Version Control: Git
Office Suites: Microsoft Office (Word, Excel, PowerPoint, Visio)
Completed Python Web Development certification Network Academy.
Attained the highest ratings in all appraisals Syntel.
Achieved certification in Data Analytics.
Recognized with the "Syntel Kudos Award" for exceptional performance as a trainee.
Received SPOT recognition and appreciation from customers and managers for outstanding contributions.
Achieved the Entrepreneurial Award from the Achievers club for innovative work.
Business Intelligence | Covid-19 Cases and Death Trends
Created interactive and informative dashboards using Power BI and Tableau to visualize the progression of
COVID-19 cases and fatalities in the United States.
Provided stakeholders with a holistic view of pandemic trends, facilitating data-driven decision-making
processes.
Data Mining | Classification Model Analysis
Conducted in-depth analysis on the UCI Adult dataset, employing advanced classification models and data
preprocessing techniques.
Developed and fine-tuned classification models using machine learning algorithms such as Random Forest,
Support Vector Machines, and Gradient Boosting, achieving high accuracy rates in predicting income levels.
Machine Learning | Spam Classification
Implemented a spam filter using Support Vector Machine (SVM) with a linear kernel, achieving high accuracy
rates in spam classification.
Enhanced accuracy through preprocessing techniques such as stemming, normalization, and feature extraction
using Text Analytics methods.
Masters in computer science Aug. 2022 Dec. 2023
Kennesaw State University, Georgia, USA
Bachelor of Technology June 2017 May 2021
KL University, India
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